Overview

Brought to you by YData

Dataset statistics

Number of variables18
Number of observations12205
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 MiB
Average record size in memory239.1 B

Variable types

Numeric14
Categorical2
Boolean2

Alerts

Administrative is highly overall correlated with Administrative_DurationHigh correlation
Administrative_Duration is highly overall correlated with AdministrativeHigh correlation
BounceRates is highly overall correlated with ExitRatesHigh correlation
ExitRates is highly overall correlated with BounceRates and 1 other fieldsHigh correlation
Informational is highly overall correlated with Informational_DurationHigh correlation
Informational_Duration is highly overall correlated with InformationalHigh correlation
ProductRelated is highly overall correlated with ExitRates and 1 other fieldsHigh correlation
ProductRelated_Duration is highly overall correlated with ProductRelatedHigh correlation
VisitorType is highly imbalanced (59.8%) Imbalance
Administrative has 5643 (46.2%) zeros Zeros
Administrative_Duration has 5778 (47.3%) zeros Zeros
Informational has 9574 (78.4%) zeros Zeros
Informational_Duration has 9800 (80.3%) zeros Zeros
ProductRelated_Duration has 630 (5.2%) zeros Zeros
BounceRates has 5518 (45.2%) zeros Zeros
PageValues has 9475 (77.6%) zeros Zeros
SpecialDay has 10956 (89.8%) zeros Zeros

Reproduction

Analysis started2025-04-18 15:15:12.389278
Analysis finished2025-04-18 15:18:50.817418
Duration3 minutes and 38.43 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Administrative
Real number (ℝ)

High correlation  Zeros 

Distinct27
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3388775
Minimum0
Maximum27
Zeros5643
Zeros (%)46.2%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:18:52.007073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile9
Maximum27
Range27
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.3304363
Coefficient of variation (CV)1.4239465
Kurtosis4.641357
Mean2.3388775
Median Absolute Deviation (MAD)1
Skewness1.9471232
Sum28546
Variance11.091806
MonotonicityNot monotonic
2025-04-18T15:18:52.853818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 5643
46.2%
1 1354
 
11.1%
2 1114
 
9.1%
3 915
 
7.5%
4 765
 
6.3%
5 575
 
4.7%
6 432
 
3.5%
7 338
 
2.8%
8 287
 
2.4%
9 225
 
1.8%
Other values (17) 557
 
4.6%
ValueCountFrequency (%)
0 5643
46.2%
1 1354
 
11.1%
2 1114
 
9.1%
3 915
 
7.5%
4 765
 
6.3%
5 575
 
4.7%
6 432
 
3.5%
7 338
 
2.8%
8 287
 
2.4%
9 225
 
1.8%
ValueCountFrequency (%)
27 1
 
< 0.1%
26 1
 
< 0.1%
24 4
 
< 0.1%
23 3
 
< 0.1%
22 4
 
< 0.1%
21 2
 
< 0.1%
20 2
 
< 0.1%
19 6
 
< 0.1%
18 12
0.1%
17 16
0.1%

Administrative_Duration
Real number (ℝ)

High correlation  Zeros 

Distinct3335
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.646331
Minimum0
Maximum3398.75
Zeros5778
Zeros (%)47.3%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:18:53.672205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median9
Q394.7
95-th percentile352.2081
Maximum3398.75
Range3398.75
Interquartile range (IQR)94.7

Descriptive statistics

Standard deviation177.49185
Coefficient of variation (CV)2.1739109
Kurtosis50.136788
Mean81.646331
Median Absolute Deviation (MAD)9
Skewness5.5921516
Sum996493.47
Variance31503.355
MonotonicityNot monotonic
2025-04-18T15:18:54.500418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5778
47.3%
4 56
 
0.5%
5 53
 
0.4%
7 45
 
0.4%
11 42
 
0.3%
6 41
 
0.3%
14 37
 
0.3%
9 35
 
0.3%
15 33
 
0.3%
10 32
 
0.3%
Other values (3325) 6053
49.6%
ValueCountFrequency (%)
0 5778
47.3%
1.333333333 1
 
< 0.1%
2 15
 
0.1%
3 26
 
0.2%
3.5 4
 
< 0.1%
4 56
 
0.5%
4.333333333 1
 
< 0.1%
4.5 2
 
< 0.1%
4.75 1
 
< 0.1%
5 53
 
0.4%
ValueCountFrequency (%)
3398.75 1
< 0.1%
2720.5 1
< 0.1%
2657.318056 1
< 0.1%
2629.253968 1
< 0.1%
2407.42381 1
< 0.1%
2156.166667 1
< 0.1%
2137.112745 1
< 0.1%
2086.75 1
< 0.1%
2047.234848 1
< 0.1%
1951.279141 1
< 0.1%

Informational
Real number (ℝ)

High correlation  Zeros 

Distinct17
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.50872593
Minimum0
Maximum24
Zeros9574
Zeros (%)78.4%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:18:55.172158image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2756166
Coefficient of variation (CV)2.5074731
Kurtosis26.659273
Mean0.50872593
Median Absolute Deviation (MAD)0
Skewness4.0141728
Sum6209
Variance1.6271977
MonotonicityNot monotonic
2025-04-18T15:18:55.770373image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 9574
78.4%
1 1041
 
8.5%
2 728
 
6.0%
3 380
 
3.1%
4 222
 
1.8%
5 99
 
0.8%
6 78
 
0.6%
7 36
 
0.3%
9 15
 
0.1%
8 14
 
0.1%
Other values (7) 18
 
0.1%
ValueCountFrequency (%)
0 9574
78.4%
1 1041
 
8.5%
2 728
 
6.0%
3 380
 
3.1%
4 222
 
1.8%
5 99
 
0.8%
6 78
 
0.6%
7 36
 
0.3%
8 14
 
0.1%
9 15
 
0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
16 1
 
< 0.1%
14 2
 
< 0.1%
13 1
 
< 0.1%
12 5
 
< 0.1%
11 1
 
< 0.1%
10 7
 
0.1%
9 15
0.1%
8 14
 
0.1%
7 36
0.3%

Informational_Duration
Real number (ℝ)

High correlation  Zeros 

Distinct1258
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.825454
Minimum0
Maximum2549.375
Zeros9800
Zeros (%)80.3%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:18:56.924995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile199
Maximum2549.375
Range2549.375
Interquartile range (IQR)0

Descriptive statistics

Standard deviation141.42481
Coefficient of variation (CV)4.0609609
Kurtosis75.534235
Mean34.825454
Median Absolute Deviation (MAD)0
Skewness7.5402906
Sum425044.67
Variance20000.976
MonotonicityNot monotonic
2025-04-18T15:18:58.063639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9800
80.3%
9 33
 
0.3%
10 26
 
0.2%
6 26
 
0.2%
7 26
 
0.2%
13 23
 
0.2%
12 23
 
0.2%
16 22
 
0.2%
8 22
 
0.2%
11 21
 
0.2%
Other values (1248) 2183
 
17.9%
ValueCountFrequency (%)
0 9800
80.3%
1 3
 
< 0.1%
1.5 1
 
< 0.1%
2 11
 
0.1%
2.5 1
 
< 0.1%
3 16
 
0.1%
3.5 1
 
< 0.1%
4 17
 
0.1%
5 18
 
0.1%
5.5 3
 
< 0.1%
ValueCountFrequency (%)
2549.375 1
< 0.1%
2256.916667 1
< 0.1%
2252.033333 1
< 0.1%
2195.3 1
< 0.1%
2166.5 1
< 0.1%
2050.433333 1
< 0.1%
1949.166667 1
< 0.1%
1830.5 1
< 0.1%
1779.166667 1
< 0.1%
1778 1
< 0.1%

ProductRelated
Real number (ℝ)

High correlation 

Distinct311
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.045637
Minimum0
Maximum705
Zeros38
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:18:58.770257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q18
median18
Q338
95-th percentile110
Maximum705
Range705
Interquartile range (IQR)30

Descriptive statistics

Standard deviation44.593649
Coefficient of variation (CV)1.3915669
Kurtosis31.072712
Mean32.045637
Median Absolute Deviation (MAD)13
Skewness4.3334194
Sum391117
Variance1988.5935
MonotonicityNot monotonic
2025-04-18T15:18:59.520265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 504
 
4.1%
3 458
 
3.8%
2 458
 
3.8%
4 404
 
3.3%
6 396
 
3.2%
7 391
 
3.2%
5 382
 
3.1%
8 370
 
3.0%
10 330
 
2.7%
9 317
 
2.6%
Other values (301) 8195
67.1%
ValueCountFrequency (%)
0 38
 
0.3%
1 504
4.1%
2 458
3.8%
3 458
3.8%
4 404
3.3%
5 382
3.1%
6 396
3.2%
7 391
3.2%
8 370
3.0%
9 317
2.6%
ValueCountFrequency (%)
705 1
< 0.1%
686 1
< 0.1%
584 1
< 0.1%
534 1
< 0.1%
518 1
< 0.1%
517 1
< 0.1%
501 1
< 0.1%
486 1
< 0.1%
470 1
< 0.1%
449 1
< 0.1%

ProductRelated_Duration
Real number (ℝ)

High correlation  Zeros 

Distinct9551
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1206.9825
Minimum0
Maximum63973.522
Zeros630
Zeros (%)5.2%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:19:00.252519image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1193
median608.94286
Q31477.1548
95-th percentile4312.9563
Maximum63973.522
Range63973.522
Interquartile range (IQR)1284.1548

Descriptive statistics

Standard deviation1919.6014
Coefficient of variation (CV)1.5904137
Kurtosis136.68145
Mean1206.9825
Median Absolute Deviation (MAD)502.44286
Skewness7.2531611
Sum14731221
Variance3684869.5
MonotonicityNot monotonic
2025-04-18T15:19:01.248245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 630
 
5.2%
17 21
 
0.2%
11 17
 
0.1%
8 17
 
0.1%
15 16
 
0.1%
12 15
 
0.1%
22 15
 
0.1%
19 15
 
0.1%
13 14
 
0.1%
7 14
 
0.1%
Other values (9541) 11431
93.7%
ValueCountFrequency (%)
0 630
5.2%
0.5 1
 
< 0.1%
1 2
 
< 0.1%
2.333333333 1
 
< 0.1%
2.666666667 1
 
< 0.1%
3 5
 
< 0.1%
4 10
 
0.1%
5 13
 
0.1%
5.333333333 1
 
< 0.1%
6 5
 
< 0.1%
ValueCountFrequency (%)
63973.52223 1
< 0.1%
43171.23338 1
< 0.1%
29970.46597 1
< 0.1%
27009.85943 1
< 0.1%
24844.1562 1
< 0.1%
23888.81 1
< 0.1%
23342.08205 1
< 0.1%
23050.10414 1
< 0.1%
21857.04648 1
< 0.1%
21672.24425 1
< 0.1%

BounceRates
Real number (ℝ)

High correlation  Zeros 

Distinct1872
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.020370317
Minimum0
Maximum0.2
Zeros5518
Zeros (%)45.2%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:19:02.469742image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.002898551
Q30.016666667
95-th percentile0.14933333
Maximum0.2
Range0.2
Interquartile range (IQR)0.016666667

Descriptive statistics

Standard deviation0.045255441
Coefficient of variation (CV)2.2216365
Kurtosis9.3339878
Mean0.020370317
Median Absolute Deviation (MAD)0.002898551
Skewness3.1624251
Sum248.61972
Variance0.0020480549
MonotonicityNot monotonic
2025-04-18T15:19:03.722767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5518
45.2%
0.2 575
 
4.7%
0.066666667 134
 
1.1%
0.028571429 115
 
0.9%
0.05 113
 
0.9%
0.033333333 101
 
0.8%
0.025 100
 
0.8%
0.016666667 99
 
0.8%
0.1 98
 
0.8%
0.04 96
 
0.8%
Other values (1862) 5256
43.1%
ValueCountFrequency (%)
0 5518
45.2%
2.73 × 10-51
 
< 0.1%
3.35 × 10-51
 
< 0.1%
3.83 × 10-51
 
< 0.1%
3.94 × 10-51
 
< 0.1%
7.09 × 10-51
 
< 0.1%
7.27 × 10-51
 
< 0.1%
7.5 × 10-51
 
< 0.1%
8.01 × 10-51
 
< 0.1%
8.08 × 10-51
 
< 0.1%
ValueCountFrequency (%)
0.2 575
4.7%
0.183333333 1
 
< 0.1%
0.18 5
 
< 0.1%
0.176923077 1
 
< 0.1%
0.175 1
 
< 0.1%
0.166666667 4
 
< 0.1%
0.164285714 1
 
< 0.1%
0.164230769 1
 
< 0.1%
0.161904762 1
 
< 0.1%
0.16 3
 
< 0.1%

ExitRates
Real number (ℝ)

High correlation 

Distinct4777
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.041465596
Minimum0
Maximum0.2
Zeros76
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:19:04.728225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.004545455
Q10.014230973
median0.025
Q30.048529412
95-th percentile0.17371429
Maximum0.2
Range0.2
Interquartile range (IQR)0.034298439

Descriptive statistics

Standard deviation0.046162702
Coefficient of variation (CV)1.1132772
Kurtosis4.6420704
Mean0.041465596
Median Absolute Deviation (MAD)0.013888889
Skewness2.2346447
Sum506.0876
Variance0.0021309951
MonotonicityNot monotonic
2025-04-18T15:19:05.494860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2 585
 
4.8%
0.1 338
 
2.8%
0.05 329
 
2.7%
0.033333333 291
 
2.4%
0.066666667 267
 
2.2%
0.025 224
 
1.8%
0.04 214
 
1.8%
0.016666667 181
 
1.5%
0.02 167
 
1.4%
0.022222222 152
 
1.2%
Other values (4767) 9457
77.5%
ValueCountFrequency (%)
0 76
0.6%
0.000175593 1
 
< 0.1%
0.000250438 1
 
< 0.1%
0.000262123 1
 
< 0.1%
0.000263158 1
 
< 0.1%
0.000292398 1
 
< 0.1%
0.000409836 1
 
< 0.1%
0.000446429 1
 
< 0.1%
0.000468384 1
 
< 0.1%
0.000480769 1
 
< 0.1%
ValueCountFrequency (%)
0.2 585
4.8%
0.192307692 1
 
< 0.1%
0.188888889 2
 
< 0.1%
0.186666667 4
 
< 0.1%
0.183333333 2
 
< 0.1%
0.181818182 1
 
< 0.1%
0.18034188 1
 
< 0.1%
0.18 3
 
< 0.1%
0.177777778 5
 
< 0.1%
0.175 6
 
< 0.1%

PageValues
Real number (ℝ)

Zeros 

Distinct2704
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.9495739
Minimum0
Maximum361.76374
Zeros9475
Zeros (%)77.6%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:19:06.197661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile38.301457
Maximum361.76374
Range361.76374
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.653671
Coefficient of variation (CV)3.1352953
Kurtosis64.998027
Mean5.9495739
Median Absolute Deviation (MAD)0
Skewness6.3509827
Sum72614.549
Variance347.95945
MonotonicityNot monotonic
2025-04-18T15:19:06.964326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9475
77.6%
53.988 6
 
< 0.1%
42.29306752 3
 
< 0.1%
40.27815244 2
 
< 0.1%
54.98 2
 
< 0.1%
58.9241766 2
 
< 0.1%
44.89345937 2
 
< 0.1%
59.988 2
 
< 0.1%
6.221045455 2
 
< 0.1%
12.55885714 2
 
< 0.1%
Other values (2694) 2707
 
22.2%
ValueCountFrequency (%)
0 9475
77.6%
0.038034542 1
 
< 0.1%
0.067049546 1
 
< 0.1%
0.093546949 1
 
< 0.1%
0.098621403 1
 
< 0.1%
0.120699914 1
 
< 0.1%
0.129676893 1
 
< 0.1%
0.131837013 1
 
< 0.1%
0.139200623 1
 
< 0.1%
0.150650498 1
 
< 0.1%
ValueCountFrequency (%)
361.7637419 1
< 0.1%
360.9533839 1
< 0.1%
287.9537928 1
< 0.1%
270.7846931 1
< 0.1%
261.4912857 1
< 0.1%
258.5498732 1
< 0.1%
255.5691579 1
< 0.1%
254.6071579 1
< 0.1%
246.7585902 1
< 0.1%
239.98 1
< 0.1%

SpecialDay
Real number (ℝ)

Zeros 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.061941827
Minimum0
Maximum1
Zeros10956
Zeros (%)89.8%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:19:07.532706image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.6
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.19966622
Coefficient of variation (CV)3.2234474
Kurtosis9.7976461
Mean0.061941827
Median Absolute Deviation (MAD)0
Skewness3.2859019
Sum756
Variance0.039866599
MonotonicityNot monotonic
2025-04-18T15:19:07.964347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 10956
89.8%
0.6 350
 
2.9%
0.8 324
 
2.7%
0.4 243
 
2.0%
0.2 178
 
1.5%
1 154
 
1.3%
ValueCountFrequency (%)
0 10956
89.8%
0.2 178
 
1.5%
0.4 243
 
2.0%
0.6 350
 
2.9%
0.8 324
 
2.7%
1 154
 
1.3%
ValueCountFrequency (%)
1 154
 
1.3%
0.8 324
 
2.7%
0.6 350
 
2.9%
0.4 243
 
2.0%
0.2 178
 
1.5%
0 10956
89.8%

Month
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size715.4 KiB
May
3329 
Nov
2982 
Mar
1860 
Dec
1706 
Oct
549 
Other values (5)
1779 

Length

Max length4
Median length3
Mean length3.0233511
Min length3

Characters and Unicode

Total characters36900
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFeb
2nd rowFeb
3rd rowFeb
4th rowFeb
5th rowFeb

Common Values

ValueCountFrequency (%)
May 3329
27.3%
Nov 2982
24.4%
Mar 1860
15.2%
Dec 1706
14.0%
Oct 549
 
4.5%
Sep 448
 
3.7%
Aug 433
 
3.5%
Jul 432
 
3.5%
June 285
 
2.3%
Feb 181
 
1.5%

Length

2025-04-18T15:19:08.546935image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-18T15:19:09.221531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
may 3329
27.3%
nov 2982
24.4%
mar 1860
15.2%
dec 1706
14.0%
oct 549
 
4.5%
sep 448
 
3.7%
aug 433
 
3.5%
jul 432
 
3.5%
june 285
 
2.3%
feb 181
 
1.5%

Most occurring characters

ValueCountFrequency (%)
M 5189
14.1%
a 5189
14.1%
y 3329
9.0%
N 2982
8.1%
o 2982
8.1%
v 2982
8.1%
e 2620
7.1%
c 2255
 
6.1%
r 1860
 
5.0%
D 1706
 
4.6%
Other values (12) 5806
15.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 36900
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
M 5189
14.1%
a 5189
14.1%
y 3329
9.0%
N 2982
8.1%
o 2982
8.1%
v 2982
8.1%
e 2620
7.1%
c 2255
 
6.1%
r 1860
 
5.0%
D 1706
 
4.6%
Other values (12) 5806
15.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 36900
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
M 5189
14.1%
a 5189
14.1%
y 3329
9.0%
N 2982
8.1%
o 2982
8.1%
v 2982
8.1%
e 2620
7.1%
c 2255
 
6.1%
r 1860
 
5.0%
D 1706
 
4.6%
Other values (12) 5806
15.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 36900
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
M 5189
14.1%
a 5189
14.1%
y 3329
9.0%
N 2982
8.1%
o 2982
8.1%
v 2982
8.1%
e 2620
7.1%
c 2255
 
6.1%
r 1860
 
5.0%
D 1706
 
4.6%
Other values (12) 5806
15.7%

OperatingSystems
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1242114
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:19:09.840377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile3
Maximum8
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.90682323
Coefficient of variation (CV)0.42689877
Kurtosis10.278024
Mean2.1242114
Median Absolute Deviation (MAD)0
Skewness2.0326127
Sum25926
Variance0.82232838
MonotonicityNot monotonic
2025-04-18T15:19:10.273814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 6541
53.6%
1 2549
 
20.9%
3 2530
 
20.7%
4 478
 
3.9%
8 75
 
0.6%
6 19
 
0.2%
7 7
 
0.1%
5 6
 
< 0.1%
ValueCountFrequency (%)
1 2549
 
20.9%
2 6541
53.6%
3 2530
 
20.7%
4 478
 
3.9%
5 6
 
< 0.1%
6 19
 
0.2%
7 7
 
0.1%
8 75
 
0.6%
ValueCountFrequency (%)
8 75
 
0.6%
7 7
 
0.1%
6 19
 
0.2%
5 6
 
< 0.1%
4 478
 
3.9%
3 2530
 
20.7%
2 6541
53.6%
1 2549
 
20.9%

Browser
Real number (ℝ)

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3578042
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:19:10.722915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile5
Maximum13
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7101139
Coefficient of variation (CV)0.72529936
Kurtosis12.553627
Mean2.3578042
Median Absolute Deviation (MAD)0
Skewness3.217404
Sum28777
Variance2.9244894
MonotonicityNot monotonic
2025-04-18T15:19:11.180217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2 7883
64.6%
1 2427
 
19.9%
4 731
 
6.0%
5 465
 
3.8%
6 174
 
1.4%
10 163
 
1.3%
8 135
 
1.1%
3 105
 
0.9%
13 56
 
0.5%
7 49
 
0.4%
Other values (3) 17
 
0.1%
ValueCountFrequency (%)
1 2427
 
19.9%
2 7883
64.6%
3 105
 
0.9%
4 731
 
6.0%
5 465
 
3.8%
6 174
 
1.4%
7 49
 
0.4%
8 135
 
1.1%
9 1
 
< 0.1%
10 163
 
1.3%
ValueCountFrequency (%)
13 56
 
0.5%
12 10
 
0.1%
11 6
 
< 0.1%
10 163
 
1.3%
9 1
 
< 0.1%
8 135
 
1.1%
7 49
 
0.4%
6 174
 
1.4%
5 465
3.8%
4 731
6.0%

Region
Real number (ℝ)

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1532978
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:19:11.611236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile8
Maximum9
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.40234
Coefficient of variation (CV)0.76185
Kurtosis-0.15996163
Mean3.1532978
Median Absolute Deviation (MAD)2
Skewness0.97848029
Sum38486
Variance5.7712373
MonotonicityNot monotonic
2025-04-18T15:19:12.043470image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 4714
38.6%
3 2379
19.5%
4 1171
 
9.6%
2 1128
 
9.2%
6 801
 
6.6%
7 758
 
6.2%
9 505
 
4.1%
8 431
 
3.5%
5 318
 
2.6%
ValueCountFrequency (%)
1 4714
38.6%
2 1128
 
9.2%
3 2379
19.5%
4 1171
 
9.6%
5 318
 
2.6%
6 801
 
6.6%
7 758
 
6.2%
8 431
 
3.5%
9 505
 
4.1%
ValueCountFrequency (%)
9 505
 
4.1%
8 431
 
3.5%
7 758
 
6.2%
6 801
 
6.6%
5 318
 
2.6%
4 1171
 
9.6%
3 2379
19.5%
2 1128
 
9.2%
1 4714
38.6%

TrafficType
Real number (ℝ)

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0739041
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size190.7 KiB
2025-04-18T15:19:13.074299image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q34
95-th percentile13
Maximum20
Range19
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.0166539
Coefficient of variation (CV)0.98594708
Kurtosis3.4654446
Mean4.0739041
Median Absolute Deviation (MAD)1
Skewness1.9585136
Sum49722
Variance16.133509
MonotonicityNot monotonic
2025-04-18T15:19:13.576526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
2 3911
32.0%
1 2388
19.6%
3 2013
16.5%
4 1066
 
8.7%
13 728
 
6.0%
10 450
 
3.7%
6 443
 
3.6%
8 343
 
2.8%
5 260
 
2.1%
11 247
 
2.0%
Other values (10) 356
 
2.9%
ValueCountFrequency (%)
1 2388
19.6%
2 3911
32.0%
3 2013
16.5%
4 1066
 
8.7%
5 260
 
2.1%
6 443
 
3.6%
7 40
 
0.3%
8 343
 
2.8%
9 41
 
0.3%
10 450
 
3.7%
ValueCountFrequency (%)
20 193
 
1.6%
19 17
 
0.1%
18 10
 
0.1%
17 1
 
< 0.1%
16 3
 
< 0.1%
15 37
 
0.3%
14 13
 
0.1%
13 728
6.0%
12 1
 
< 0.1%
11 247
 
2.0%

VisitorType
Categorical

Imbalance 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size871.1 KiB
Returning_Visitor
10431 
New_Visitor
1693 
Other
 
81

Length

Max length17
Median length17
Mean length16.088079
Min length5

Characters and Unicode

Total characters196355
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReturning_Visitor
2nd rowReturning_Visitor
3rd rowReturning_Visitor
4th rowReturning_Visitor
5th rowReturning_Visitor

Common Values

ValueCountFrequency (%)
Returning_Visitor 10431
85.5%
New_Visitor 1693
 
13.9%
Other 81
 
0.7%

Length

2025-04-18T15:19:14.137483image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-18T15:19:14.495384image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
returning_visitor 10431
85.5%
new_visitor 1693
 
13.9%
other 81
 
0.7%

Most occurring characters

ValueCountFrequency (%)
i 34679
17.7%
t 22636
11.5%
r 22636
11.5%
n 20862
10.6%
e 12205
 
6.2%
s 12124
 
6.2%
V 12124
 
6.2%
_ 12124
 
6.2%
o 12124
 
6.2%
g 10431
 
5.3%
Other values (6) 24410
12.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 196355
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 34679
17.7%
t 22636
11.5%
r 22636
11.5%
n 20862
10.6%
e 12205
 
6.2%
s 12124
 
6.2%
V 12124
 
6.2%
_ 12124
 
6.2%
o 12124
 
6.2%
g 10431
 
5.3%
Other values (6) 24410
12.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 196355
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 34679
17.7%
t 22636
11.5%
r 22636
11.5%
n 20862
10.6%
e 12205
 
6.2%
s 12124
 
6.2%
V 12124
 
6.2%
_ 12124
 
6.2%
o 12124
 
6.2%
g 10431
 
5.3%
Other values (6) 24410
12.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 196355
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 34679
17.7%
t 22636
11.5%
r 22636
11.5%
n 20862
10.6%
e 12205
 
6.2%
s 12124
 
6.2%
V 12124
 
6.2%
_ 12124
 
6.2%
o 12124
 
6.2%
g 10431
 
5.3%
Other values (6) 24410
12.4%

Weekend
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size107.3 KiB
False
9346 
True
2859 
ValueCountFrequency (%)
False 9346
76.6%
True 2859
 
23.4%
2025-04-18T15:19:14.782321image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Revenue
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size107.3 KiB
False
10297 
True
1908 
ValueCountFrequency (%)
False 10297
84.4%
True 1908
 
15.6%
2025-04-18T15:19:15.030404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Interactions

2025-04-18T15:18:24.569914image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:25.410165image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:38.071428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:48.704692image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:57.119877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:06.217773image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:15.399508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:27.463530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:36.973041image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:47.543340image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:58.678895image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:20.187664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:41.219349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:06.767215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:25.897260image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:26.552897image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:38.675594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:49.254709image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:57.752946image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:06.835992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:16.715074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:28.037202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:37.628934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:48.513391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:59.817707image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:21.859194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:43.344371image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:08.168687image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:26.988620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:27.183657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:39.286273image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:49.875082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:58.354193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:07.525957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:17.383501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:28.680014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:38.359885image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:49.794285image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:00.436413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:23.222660image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:45.781377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:10.191600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:27.775417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:28.033128image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:39.860449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:50.436634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:58.938247image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:08.150752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:18.695103image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:29.305639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:39.011046image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:50.982077image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:01.647044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:25.212094image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:47.686253image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:11.450315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:29.426539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:29.469769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:40.474486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:50.987981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:59.511841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:08.790551image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:20.385946image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:29.916200image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:39.669861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:51.593202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:03.216980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:26.956856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:50.204237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:12.309698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:30.944039image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:31.168917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:42.538420image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:51.589863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:00.168068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:09.434977image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:21.048481image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:30.548212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:40.376726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:52.172908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:04.922433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:28.505267image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:52.830640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:13.160135image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:31.945830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:31.957861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:43.295967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:52.216160image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:00.924962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:10.081553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:21.627664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:31.195858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:41.054250image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:52.779336image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:06.362829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:30.226149image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:55.119443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:14.618436image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:34.295091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:32.562796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:43.952337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:52.874524image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:01.606663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:10.793053image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:22.253893image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:31.846197image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:41.727602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:53.435682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:07.940921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:31.813349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:57.448900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:16.236947image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:36.178507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:33.140333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:44.630359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:53.519103image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:02.451429image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:11.484366image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:22.894271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:32.495914image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:42.395824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:54.143496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:09.390586image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:32.892810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:59.821919image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:17.232147image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:37.743102image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:33.708165image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:45.240865image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:54.120377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:03.169911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:12.168698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:23.497585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:33.320293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:43.094879image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:55.359679image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:10.709182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:34.422894image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:01.988108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:18.169129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:40.005514image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:34.500412image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:45.872221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:54.710981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:03.770282image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:12.909006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:24.066211image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:34.079094image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:43.743410image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:56.278060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:11.869462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:35.669192image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:03.203647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:18.989388image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:41.728673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:35.716812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:46.629706image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:55.327931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:04.408313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:13.557809image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:25.621617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:34.899408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:44.416563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:56.941094image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:13.547594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:36.821537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:04.194356image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:20.012379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:43.176849image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:36.347551image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:47.347856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:55.902952image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:04.968260image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:14.156094image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:26.231551image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:35.578477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:45.060392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:57.495173image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:15.351748image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:37.991744image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:04.935018image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:21.280839image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:44.593017image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:37.428156image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:48.006359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:15:56.513334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:05.591293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:14.780239image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:26.846514image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:36.251369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:45.915513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:16:58.093438image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:17.757350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:17:39.384648image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:05.784541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-18T15:18:23.272053image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-04-18T15:19:15.445547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
AdministrativeAdministrative_DurationBounceRatesBrowserExitRatesInformationalInformational_DurationMonthOperatingSystemsPageValuesProductRelatedProductRelated_DurationRegionRevenueSpecialDayTrafficTypeVisitorTypeWeekend
Administrative1.0000.939-0.140-0.015-0.4250.3670.3600.050-0.0060.3250.4520.4130.0070.128-0.129-0.0160.0850.025
Administrative_Duration0.9391.000-0.149-0.026-0.4290.3540.3500.019-0.0090.3140.4220.4050.0160.063-0.135-0.0190.0080.000
BounceRates-0.140-0.1491.000-0.0440.5890.0160.0070.0540.057-0.116-0.022-0.050-0.0130.1650.1430.0230.1190.042
Browser-0.015-0.026-0.0441.000-0.013-0.022-0.0150.0570.3700.0250.0400.0430.0550.0400.020-0.0020.4630.058
ExitRates-0.425-0.4290.589-0.0131.000-0.180-0.1950.0580.025-0.304-0.504-0.4610.0010.2410.1590.0290.1820.059
Informational0.3670.3540.016-0.022-0.1801.0000.9510.017-0.0010.2170.3660.365-0.0250.076-0.056-0.0310.0290.010
Informational_Duration0.3600.3500.007-0.015-0.1950.9511.0000.0080.0020.2220.3580.360-0.0170.067-0.056-0.0290.0090.000
Month0.0500.0190.0540.0570.0580.0170.0081.0000.0550.0180.0680.0460.0360.1730.2380.1590.1340.059
OperatingSystems-0.006-0.0090.0570.3700.025-0.0010.0020.0551.000-0.0130.0190.0210.0250.0750.0220.0790.4530.117
PageValues0.3250.314-0.1160.025-0.3040.2170.2220.018-0.0131.0000.3380.357-0.0000.413-0.072-0.0200.1110.031
ProductRelated0.4520.422-0.0220.040-0.5040.3660.3580.0680.0190.3381.0000.879-0.0260.125-0.027-0.0780.0800.000
ProductRelated_Duration0.4130.405-0.0500.043-0.4610.3650.3600.0460.0210.3570.8791.000-0.0150.071-0.055-0.0800.0360.004
Region0.0070.016-0.0130.0550.001-0.025-0.0170.0360.025-0.000-0.026-0.0151.0000.012-0.015-0.0070.1720.015
Revenue0.1280.0630.1650.0400.2410.0760.0670.1730.0750.4130.1250.0710.0121.0000.0870.1200.1030.026
SpecialDay-0.129-0.1350.1430.0200.159-0.056-0.0560.2380.022-0.072-0.027-0.055-0.0150.0871.0000.1110.0650.260
TrafficType-0.016-0.0190.023-0.0020.029-0.031-0.0290.1590.079-0.020-0.078-0.080-0.0070.1200.1111.0000.3060.091
VisitorType0.0850.0080.1190.4630.1820.0290.0090.1340.4530.1110.0800.0360.1720.1030.0650.3061.0000.052
Weekend0.0250.0000.0420.0580.0590.0100.0000.0590.1170.0310.0000.0040.0150.0260.2600.0910.0521.000

Missing values

2025-04-18T15:18:46.496978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-04-18T15:18:48.146033image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

AdministrativeAdministrative_DurationInformationalInformational_DurationProductRelatedProductRelated_DurationBounceRatesExitRatesPageValuesSpecialDayMonthOperatingSystemsBrowserRegionTrafficTypeVisitorTypeWeekendRevenue
000.000.010.0000000.2000000.2000000.00.0Feb1111Returning_VisitorFalseFalse
100.000.0264.0000000.0000000.1000000.00.0Feb2212Returning_VisitorFalseFalse
200.000.010.0000000.2000000.2000000.00.0Feb4193Returning_VisitorFalseFalse
300.000.022.6666670.0500000.1400000.00.0Feb3224Returning_VisitorFalseFalse
400.000.010627.5000000.0200000.0500000.00.0Feb3314Returning_VisitorTrueFalse
500.000.019154.2166670.0157890.0245610.00.0Feb2213Returning_VisitorFalseFalse
600.000.010.0000000.2000000.2000000.00.4Feb2433Returning_VisitorFalseFalse
710.000.000.0000000.2000000.2000000.00.0Feb1215Returning_VisitorTrueFalse
800.000.0237.0000000.0000000.1000000.00.8Feb2223Returning_VisitorFalseFalse
900.000.03738.0000000.0000000.0222220.00.4Feb2412Returning_VisitorFalseFalse
AdministrativeAdministrative_DurationInformationalInformational_DurationProductRelatedProductRelated_DurationBounceRatesExitRatesPageValuesSpecialDayMonthOperatingSystemsBrowserRegionTrafficTypeVisitorTypeWeekendRevenue
1232000.0000.08143.5833330.0142860.0500000.0000000.0Nov2231Returning_VisitorFalseFalse
1232100.0000.060.0000000.2000000.2000000.0000000.0Nov1841Returning_VisitorFalseFalse
12322676.2500.0221075.2500000.0000000.0041670.0000000.0Dec2242Returning_VisitorFalseFalse
12323264.7500.0441157.9761900.0000000.0139530.0000000.0Nov22110Returning_VisitorFalseFalse
1232400.0010.016503.0000000.0000000.0376470.0000000.0Nov2211Returning_VisitorFalseFalse
123253145.0000.0531783.7916670.0071430.02903112.2417170.0Dec4611Returning_VisitorTrueFalse
1232600.0000.05465.7500000.0000000.0213330.0000000.0Nov3218Returning_VisitorTrueFalse
1232700.0000.06184.2500000.0833330.0866670.0000000.0Nov32113Returning_VisitorTrueFalse
12328475.0000.015346.0000000.0000000.0210530.0000000.0Nov22311Returning_VisitorFalseFalse
1232900.0000.0321.2500000.0000000.0666670.0000000.0Nov3212New_VisitorTrueFalse